hive

Quick Start

Prerequisites

• Python 3.11+ for agent development
• An LLM provider that powers the agents
• ripgrep (optional, recommended on Windows): The search_files tool uses ripgrep for faster file search. If not installed, a Python fallback is used. On Windows: winget install BurntSushi.ripgrep or scoop install ripgrep

Windows Users: Native Windows is supported via quickstart.ps1 and hive.ps1. Run these in PowerShell 5.1+. WSL is also an option but not required.

Installation

Note Hive uses a uv workspace layout and is not installed with pip install. Running pip install -e . from the repository root will create a placeholder package and Hive will not function correctly. Please use the quickstart script below to set up the environment.

# Clone the repository
git clone https://github.com/aden-hive/hive.git
cd hive


# Run quickstart setup
./quickstart.sh

This sets up:

• framework - Core agent runtime and graph executor (in core/.venv)

• aden_tools - MCP tools for agent capabilities (in tools/.venv)

• credential store - Encrypted API key storage (~/.hive/credentials)

• LLM provider - Interactive default model configuration, including Hive LLM and OpenRouter

• All required Python dependencies with uv

• Finally, it will open the Hive interface in your browser

Tip: To reopen the dashboard later, run hive open from the project directory.

Build Your First Agent

Type the agent you want to build in the home input box. The queen is going to ask you questions and work out a solution with you.

Use Template Agents

Click "Try a sample agent" and check the templates. You can run a template directly or choose to build your version on top of the existing template.

Run Agents

Now you can run an agent by selecting the agent (either an existing agent or example agent). You can click the Run button on the top left, or talk to the queen agent and it can run the agent for you.

Features

• Browser-Use - Control the browser on your computer to achieve hard tasks
• Parallel Execution - Execute the generated graph in parallel. This way you can have multiple agents completing the jobs for you
• Goal-Driven Generation - Define objectives in natural language; the coding agent generates the agent graph and connection code to achieve them
• Adaptiveness - Framework captures failures, calibrates according to the objectives, and evolves the agent graph
• Dynamic Node Connections - No predefined edges; connection code is generated by any capable LLM based on your goals
• SDK-Wrapped Nodes - Every node gets shared memory, local RLM memory, monitoring, tools, and LLM access out of the box
• Human-in-the-Loop - Intervention nodes that pause execution for human input with configurable timeouts and escalation
• Real-time Observability - WebSocket streaming for live monitoring of agent execution, decisions, and node-to-node communication

Integration

Hive is built to be model-agnostic and system-agnostic.

• LLM flexibility - Hive Framework supports Anthropic, OpenAI, OpenRouter, Hive LLM, and other hosted or local models through LiteLLM-compatible providers.
• Business system connectivity - Hive Framework is designed to connect to all kinds of business systems as tools, such as CRM, support, messaging, data, file, and internal APIs via MCP.

Why Aden

Hive focuses on generating agents that run real business processes rather than generic agents. Instead of requiring you to manually design workflows, define agent interactions, and handle failures reactively, Hive flips the paradigm: you describe outcomes, and the system builds itself—delivering an outcome-driven, adaptive experience with an easy-to-use set of tools and integrations.

flowchart LR
    GOAL["Define Goal"] --> GEN["Auto-Generate Graph"]
    GEN --> EXEC["Execute Agents"]
    EXEC --> MON["Monitor & Observe"]
    MON --> CHECK{{"Pass?"}}
    CHECK -- "Yes" --> DONE["Deliver Result"]
    CHECK -- "No" --> EVOLVE["Evolve Graph"]
    EVOLVE --> EXEC

    GOAL -.- V1["Natural Language"]
    GEN -.- V2["Instant Architecture"]
    EXEC -.- V3["Easy Integrations"]
    MON -.- V4["Full visibility"]
    EVOLVE -.- V5["Adaptability"]
    DONE -.- V6["Reliable outcomes"]

    style GOAL fill:#ffbe42,stroke:#cc5d00,stroke-width:2px,color:#333
    style GEN fill:#ffb100,stroke:#cc5d00,stroke-width:2px,color:#333
    style EXEC fill:#ff9800,stroke:#cc5d00,stroke-width:2px,color:#fff
    style MON fill:#ff9800,stroke:#cc5d00,stroke-width:2px,color:#fff
    style CHECK fill:#fff59d,stroke:#ed8c00,stroke-width:2px,color:#333
    style DONE fill:#4caf50,stroke:#2e7d32,stroke-width:2px,color:#fff
    style EVOLVE fill:#e8763d,stroke:#cc5d00,stroke-width:2px,color:#fff
    style V1 fill:#fff,stroke:#ed8c00,stroke-